Extension of the open-source TIGRE toolbox for proton imaging.

Proton irradiation is a well-established method to treat deep-seated tumors in radio oncology. Usually, an X-ray computed tomography (CT) scan is used for treatment planning. Since proton therapy is based on the precise knowledge of the stopping power describing the energy loss of protons in the patient tissues, the Hounsfield units of the planning CT have to be converted. This conversion introduces range errors in the treatment plan, which could be reduced, if the stopping power values were extracted directly from an image obtained using protons instead of X-rays. Since protons are affected by multiple Coulomb scattering, reconstruction of the 3D stopping power map results in limited image quality if the curved proton path is not considered. This work presents a substantial code extension of the open-source toolbox TIGRE for proton CT (pCT) image reconstruction based on proton radiographs including a curved proton path estimate. The code extension and the reconstruction algorithms are GPU-based, allowing to achieve reconstruction results within minutes. The performance of the pCT code extension was tested with Monte Carlo simulated data using three phantoms (Catphan® high resolution and sensitometry modules and a CIRS patient phantom). In the simulations, ideal and non-ideal conditions for a pCT setup were assumed. The obtained mean absolute percentage error was found to be below 1% and up to 8 lp/cm could be resolved using an idealized setup. These findings demonstrate that the presented code extension to the TIGRE toolbox offers the possibility for other research groups to use a fast and accurate open-source pCT reconstruction.

Feasibility study of a proton CT system based on 4D-tracking and residual energy determination via time-of-flight.

Objective.For dose calculations in ion beam therapy, it is vital to accurately determine the relative stopping power (RSP) distribution within the treatment volume. A suitable imaging modality to achieve the required RSP accuracy is proton computed tomography (pCT), which usually uses a tracking system and a separate residual energy (or range) detector to directly measure the RSP distribution. This work investigates the potential of a novel pCT system based on a single detector technology, namely low gain avalanche detectors (LGADs). LGADs are fast 4D-tracking detectors, which can be used to simultaneously measure the particle position and time with precise timing and spatial resolution. In contrast to standard pCT systems, the residual energy is determined via a time-of-flight (TOF) measurement between different 4D-tracking stations.Approach.To show the potential of using 4D-tracking for proton imaging, we studied and optimized the design parameters for a realistic TOF-pCT system using Monte Carlo simulations. We calculated the RSP accuracy and RSP resolution inside the inserts of the CTP404 phantom and compared the results to a simulation of an ideal pCT system.Main results.After introducing a dedicated calibration procedure for the TOF calorimeter, RSP accuracies less than 0.6% could be achieved. We also identified the design parameters with the strongest impact on the RSP resolution and proposed a strategy to further improve the image quality.Significance.This comprehensive study of the most important design aspects for a novel TOF-pCT system could help guide future hardware developments and, once implemented, improve the quality of treatment planning in ion beam therapy.

Calculating 1/ß2p2 for most likely path estimates for protons and helium ions using an analytical model.

In ion computed tomography, limited spatial resolution can be related to the non-straight path of ions resulting from multiple Coulomb scattering in the object to be imaged. By including sophisticated path estimates such as most likely path (MLP) or optimized cubic spline into the image reconstruction algorithm, the achieved spatial resolution can be substantially improved compared to assuming a simple straight line path only. The typically used implementation of the MLP is a matrix-based approach employing Bayesian statistics and modelling multiple Coulomb scattering as Gaussian distribution. For the elements of the scattering matrices, the term 1/ß(w)2p(w)2, depending on the momentum and velocity of an ion within a phantom depth w, has to be known and integrated along the depth w. Usually, this term is extracted from a Monte Carlo simulation and approximated by a polynomial fit to solve the integral. In the present study, an existing analytical model for ion ranges and stopping powers was used to calculate 1/ß(w)2p(w)2 and the scattering matrices for the MLP and was tested for protons and helium ions. The model was investigated for 10 cm to 40 cm water targets and initial energies ranging from 150 MeV to 300 MeV for protons and 150 MeV/u to 300 MeV/u for helium ions. In all cases, the calculated value obtained for 1/ß(w)2p(w)2 was compared to a GATE simulation. The difference between root-mean-square errors of MLP estimates using calculated and simulated 1/ß(w)2p(w)2 values were found to be smaller than 3 µm for all investigated water targets and energies.

First application of the GPU-based software framework TIGRE for proton CT image reconstruction.

In proton therapy, the knowledge of the proton stopping power, i.e. the energy deposition per unit length within human tissue, is essential for accurate treatment planning. One suitable method to directly measure the stopping power is proton computed tomography (pCT). Due to the proton interaction mechanisms in matter, pCT image reconstruction faces some challenges: the unique path of each proton has to be considered separately in the reconstruction process adding complexity to the reconstruction problem. This study shows that the GPU-based open-source software toolkit TIGRE, which was initially intended for X-ray CT reconstruction, can be applied to the pCT image reconstruction problem using a straight line approach for the proton path. This simplified approach allows for reconstructions within seconds. To validate the applicability of TIGRE to pCT, several Monte Carlo simulations modeling a pCT setup with two Catphan® modules as phantoms were performed. Ordered-Subset Simultaneous Algebraic Reconstruction Technique (OS-SART) and Adaptive-Steepest-Descent Projection Onto Convex Sets (ASD-POCS) were used for image reconstruction. Since the accuracy of the approach is limited by the straight line approximation of the proton path, requirements for further improvement of TIGRE for pCT are addressed.